Design of Complex Engineered System and the Effectiveness of Organizational Networks

This dataset presents data collect during research for my Ph.D. dissertation in Industrial and Systems Engineering at the University of Rhode Island in 2017-2018. Research Purpose Cost and schedule overruns have become increasingly common in large defense programs that attempt to build systems with improved performance and lifecycle characteristics, often using novel, untested, and complex product architectures. Based on the well documented relationship between product architecture and the structure of the product development organization, research examined the effectiveness of different organizational networks at designing complex engineered systems, comparing the performance or real-world organizations to ideal ones. Method and Research Questions Phase 1 examined information exchange models and implemented the model of information exchange proposed by Dodds, Watts and Sabel to confirm the model can be successfully implemented using agent-based models (ABM). Phase 2 examined artifact models and extended the information exchange model to include the processing artifacts. Phase 3 examined smart team models and phase 4 applied information exchange and artifact models to a real-world organization. Research questions: 1) How do random, multi-scale, military staff and matrix organizational networks perform in the information exchange and artifact task environments and how does increasing the degree of complexity affect performance? 2) How do military staff and matrix organizational networks (real organizations) perform compared to one another and to random and multi-scale networks (ideal organizations)? How does increasing degree of complexity affect performance and which structure is preferred for organizations that design complex engineered systems? 3) How can organizational networks be modified to improve performance? Data Interpretation Excel spreadsheets summarize and analyze data collected from MATLAB and NetLogo ABM experiments for each phase. In general, raw data was collected in a 'data' worksheet, and then additional worksheets and graphs were created to analyze data. Dataset includes link to associated dissertation, which provides further detail. Notable Findings 1) All organizational networks perform well in the information exchange environment and in the artifact environment when complexity is low to moderate. 2) Military staff networks consistently out-perform matrix networks. 3) At high complexity, all networks are susceptible to congestion failure. 4) Military staff organizational networks exhibit performance comparable to multi-scale networks over a range of situations.